A tool for creating and testing compartmental epidemiological models faster than ever for the mathematical modeling of infectious diseases. An idea from https://github.com/henrifroese/infectious_disease_modelling.
Use epispot's DOI in your research! 🎆
Citation:
q9i, & QLabs. (2021, April 2). epispot/epispot: (Version 2.1.0). Zenodo. http://doi.org/10.5281/zenodo.4624423
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Epispot can be installed via pip or via Anaconda. If using pip, install with:
pip install epispotFor Anaconda, install via conda-forge as:
conda config --add channels conda-forge
conda install -c conda-forge epispotAs a shorthand, use import epispot as epi.
You can also install the epispot-nightly package from pip:
pip install epispot-nightlyYou can import it the same as import epispot as epi. Both packages cannot be used at the same time.
Start with the tutorials in tests/tutorials (see GitHub repo). Next, check out the
documentation at https://epispot.github.io/epispot. You may also find
it helpful to see the examples in the tests/examples folder.
See GitHub repo for more info.
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SIR-based models
- Susceptible
- Infected
- Recovered
- Exposed
- Dead
- Critical
- Hospitalized
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Custom-defined compartmental models
- Create custom models using the
Modelclass
- Create custom models using the
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Graphing Capabilities
- Plot real data from a
.csvfile - Plot model predictions interactively
- Compare different model predictions
- Plot real data from a
Documentation can easily be accessed from function, class, and file docstrings.
Docstrings provide additional documentation on a certain function.
They can be accessed by the built-in Python help() command.
These strings are formatted in Github-flavored markdown.
Additionally, all files will have a 'STRUCTURE' label.
The epispot package is supported by the following contributors:
- Head of Software & Development: @quantum9innovation
- Head of Code Maintenance: @Quantalabs